Search results for: edge application framework

Authors: Hyunjoo Park, Taehyun Kim, Taehyun Kim

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Human life, activity, and culture depend on the wider environment. Cities offer economic opportunities for goods and services, but cannot exist in environments without food, energy, and water supply. Technological innovation in energy supply and transport speeds up the expansion of urban areas and the physical separation from agricultural land. As a result, division of urban agricultural areas causes more energy demand for food and goods transport between the regions. As the energy resources are leaking all over the world, the impact on the environment crossing the boundaries of cities is also growing. While advances in energy and other technologies can reduce the environmental impact of consumption, there is still a gap between energy supply and demand by current technology, even in technically advanced countries. Therefore, reducing energy demand is more realistic than relying solely on the development of technology for sustainable development. The purpose of this study is to introduce the application of carbon footprint assessment in fields of urban planning and geography. In urban studies, carbon footprint has been assessed at different geographical scales, such as nation, city, region, household, and individual. Carbon footprint assessment for a nation and a city is available by using national or city level statistics of energy consumption categories. By means of carbon footprint calculation, it is possible to compare the ecological capacity and deficit among nations and cities. Carbon footprint also offers great insight on the geographical distribution of carbon intensity at a regional level in the agricultural field. The study shows the background of carbon footprint applications in urban planning and geography by case studies such as figuring out sustainable land-use measures in urban planning and geography. For micro level, footprint quiz or survey can be adapted to measure household and individual carbon footprint. For example, first case study collected carbon footprint data from the survey measuring home energy use and travel behavior of 2,064 households in eight cities in Gyeonggi-do, Korea. Second case study analyzed the effects of the net and gross population densities on carbon footprint of residents at an intra-urban scale in the capital city of Seoul, Korea. In this study, the individual carbon footprint of residents was calculated by converting the carbon intensities of home and travel fossil fuel use of respondents to the unit of metric ton of carbon dioxide (tCO₂) by multiplying the conversion factors equivalent to the carbon intensities of each energy source, such as electricity, natural gas, and gasoline. Carbon footprint is an important concept not only for reducing climate change but also for sustainable development. As seen in case studies carbon footprint may be measured and applied in various spatial units, including but not limited to countries and regions. These examples may provide new perspectives on carbon footprint application in planning and geography. In addition, additional concerns for consumption of food, goods, and services can be included in carbon footprint calculation in the area of urban planning and geography.

Keywords: carbon footprint, case study, geography, urban planning

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Authors: Kukuri Tavartkiladze, Nana Bolashvili

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The purpose of this paper was separation and study of the part of structure regime, which directly affects the process of desertification. A simple scheme was prepared for the assessment of desertification process; surface air temperature and precipitation for the years of 1936-2009 were analyzed.  The map of distribution of the Desertification Contributing Coefficient in the territory of Georgia was compiled. The simple scheme for identification of the intensity of the desertification contributing process has been developed and the illustrative example of its practical application for the territory of Georgia has been conducted.

Keywords: aridity, climate change, desertification, precipitation

Procedia PDF Downloads 322

Authors: Ali Muhammad

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The purpose of this study is to develop a theoretical framework which demonstrates the effect of four personal factors on employees rule following behavior in Kuwaiti business organizations. The model suggested in this study includes organizational citizenship behavior, affective organizational commitment, organizational trust, and procedural justice as possible predictors of rule following behavior. The study also attempts to compare the effects of the suggested factors on employees rule following behavior. The new model will, hopefully, extend previous research by adding new variables to the models used to explain employees rule following behavior. A discussion of issues related to rule-following behavior is presented, as well as recommendations for future research.

Keywords: employee adherence to rules, organizational justice, organizational commitment, organizational citizenship behavior

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Authors: Ricardo Merlo

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In this paper, we analyzed the different didactic proposals for teaching about the free fall motion of bodies available online. An important aspect was the interpretation of the direction and sense of the acceleration of gravity and of the falling velocity of a body, which is why we found different applications of the Cartesian reference system used and also different graphical presentations of the velocity as a function of time and of the distance traveled vertically by the body in the period of time that it was dropped from a height h0. In this framework, a survey of previous concepts was applied to a voluntary group of first-year university students of an Engineering degree before and after the development of the class of the subject in question. Then, Hake's index (0.52) was determined, which resulted in an average learning gain from the meaningful use of the reference system and the respective graphs of v=ƒ (t) and h=ƒ (t).

Keywords: didactic gain, free–fall, physics teaching, previous knowledge

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Authors: Sylvie Michel, Emmanuelle Gagnou, Joanne Hamet

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Researchers in the fields of AI and Robotics frequently encounter ethical dilemmas throughout their research endeavors. Various ethical challenges have been pinpointed in the existing literature, including biases and discriminatory outcomes, diffusion of responsibility, and a deficit in transparency within AI operations. This research aims to pinpoint these ethical quandaries faced by researchers and shed light on the mechanisms behind ethical decision-making in the research process. By synthesizing insights from existing literature and acknowledging prevalent shortcomings, such as overlooking the heterogeneous nature of decision-making, non-accumulative results, and a lack of consensus on numerous factors due to limited empirical research, the objective is to conceptualize and validate a model. This model will incorporate influences from individual perspectives and situational contexts, considering potential moderating factors in the ethical decision-making process. Qualitative analyses were conducted based on direct observation of an AI/Robotics research team focusing on collaborative robotics for several months. Subsequently, semi-structured interviews with 16 team members were conducted. The entire process took place during the first semester of 2023. Observations were analyzed using an analysis grid, and the interviews underwent thematic analysis using Nvivo software. An initial finding involves identifying the ethical challenges that AI/robotics researchers confront, underlining a disparity between practical applications and theoretical considerations regarding ethical dilemmas in the realm of AI. Notably, researchers in AI prioritize the publication and recognition of their work, sparking the genesis of these ethical inquiries. Furthermore, this article illustrated that researchers tend to embrace a consequentialist ethical framework concerning safety (for humans engaging with robots/AI), worker autonomy in relation to robots, and the societal implications of labor (can robots displace jobs?). A second significant contribution entails proposing a model for ethical decision-making within the AI/Robotics research sphere. The model proposed adopts a process-oriented approach, delineating various research stages (topic proposal, hypothesis formulation, experimentation, conclusion, and valorization). Across these stages and the ethical queries, they entail, a comprehensive four-point comprehension of ethical decision-making is presented: recognition of the moral quandary; moral judgment, signifying the decision-maker's aptitude to discern the morally righteous course of action; moral intention, reflecting the ability to prioritize moral values above others; and moral behavior, denoting the application of moral intention to the situation. Variables such as political inclinations ((anti)-capitalism, environmentalism, veganism) seem to wield significant influence. Moreover, age emerges as a noteworthy moderating factor. AI and robotics researchers are continually confronted with ethical dilemmas during their research endeavors, necessitating thoughtful decision-making. The contribution involves introducing a contextually tailored model, derived from meticulous observations and insightful interviews, enabling the identification of factors that shape ethical decision-making at different stages of the research process.

Keywords: ethical decision making, artificial intelligence, robotics, research

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Authors: Luís Farinha, João J. Ferreira

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Nowadays innovation represents a challenge crucial to remaining globally competitive. This study seeks to develop a conceptual model aimed at measuring the dynamic interactions of the triple/quadruple helix, balancing innovation and entrepreneurship initiatives as pillars of regional competitiveness – the Regional Helix Scoreboard (RHS). To this aim, different strands of literature are identified according to their focus on specific regional competitiveness governance mechanisms. We put forward an overview of the state-of-the-art of research and is duly assessed in order to develop and propose a framework of analysis that enables an integrated approach in the context of collaborative dynamics. We conclude by presenting the RHS for the study of regional competitiveness dynamics, which integrates and associates different backgrounds and identifies a number of key performance indicators for research challenges.

Keywords: entrepreneurship, KPIs, innovation, performance measurement, regional competitiveness, regional helix scoreboard

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Authors: Brayden Mi

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Reverse time migration has been widely used in the Petroleum exploration industry to reveal subsurface images and to detect rock and fluid properties since the early 1980s. The seismic technology involves the construction of a velocity model through interpretive model construction, seismic tomography, or full waveform inversion, and the application of the reverse-time propagation of acquired seismic data and the original wavelet used in the acquisition. The methodology has matured from 2D, simple media to present-day to handle full 3D imaging challenges in extremely complex geological conditions. Conventional Ultrasound computed tomography (USCT) utilize travel-time-inversion to reconstruct the velocity structure of an organ. With the velocity structure, USCT data can be migrated with the “bend-ray” method, also known as migration. Its seismic application counterpart is called Kirchhoff depth migration, in which the source of reflective energy is traced by ray-tracing and summed to produce a subsurface image. It is well known that ray-tracing-based migration has severe limitations in strongly heterogeneous media and irregular acquisition geometries. Reverse time migration (RTM), on the other hand, fully accounts for the wave phenomena, including multiple arrives and turning rays due to complex velocity structure. It has the capability to fully reconstruct the image detectable in its acquisition aperture. The RTM algorithms typically require a rather accurate velocity model and demand high computing powers, and may not be applicable to real-time imaging as normally required in day-to-day medical operations. However, with the improvement of computing technology, such a computational bottleneck may not present a challenge in the near future. The present-day (RTM) algorithms are typically implemented from a flat datum for the seismic industry. It can be modified to accommodate any acquisition geometry and aperture, as long as sufficient illumination is provided. Such flexibility of RTM can be conveniently implemented for the application in USCT imaging if the spatial coordinates of the transmitters and receivers are known and enough data is collected to provide full illumination. This paper proposes an implementation of a full 3D RTM algorithm for USCT imaging to produce an accurate 3D acoustic image based on the Phase-shift-plus-interpolation (PSPI) method for wavefield extrapolation. In this method, each acquired data set (shot) is propagated back in time, and a known ultrasound wavelet is propagated forward in time, with PSPI wavefield extrapolation and a piece-wise constant velocity model of the organ (breast). The imaging condition is then applied to produce a partial image. Although each image is subject to the limitation of its own illumination aperture, the stack of multiple partial images will produce a full image of the organ, with a much-reduced noise level if compared with individual partial images.

Keywords: illumination, reverse time migration (RTM), ultrasound computed tomography (USCT), wavefield extrapolation

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Authors: Ji Eun Shin, Dong Hoon Lim

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Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

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Authors: Christina Klippel, Lucia Pezzi, Silvio Neto, Rafael Bertani, Priscila Mendes, Flavio Machado, Aline Szeliga, Maria Cosendey, Adilson Mariz, Raquel Santos, Lys Bendett, Pedro Velasco, Thalita Rolleigh, Bruna Bellote, Daria Coelho, Bruna Martins, Julia Almeida, Juliana Cerqueira

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This project presents a framework for teaching intracranial pressure monitoring (ICP) concepts using a low-cost experimental model in a neurointensive care education program. Data concerning ICP monitoring contribute to the patient's clinical assessment and may dictate the course of action of a health team (nursing, medical staff) and influence decisions to determine the appropriate intervention. This study aims to present a safe method for teaching ICP monitoring to medical students in a Simulation Center. Methodology: Medical school teachers, along with students from the 4th year, built an experimental model for teaching ICP measurement. The model consists of a mannequin's head with a plastic bag inside simulating the cerebral ventricle and an inserted ventricular catheter connected to the ICP monitoring system. The bag simulating the ventricle can also be changed for others containing bloody or infected simulated cerebrospinal fluid. On the mannequin's ear, there is a blue point indicating the right place to set the "zero point" for accurate pressure reading. The educational program includes four steps: 1st - Students receive a script on ICP measurement for reading before training; 2nd - Students watch a video about the subject created in the Simulation Center demonstrating each step of the ICP monitoring and the proper care, such as: correct positioning of the patient, anatomical structures to establish the zero point for ICP measurement and a secure range of ICP; 3rd - Students train the procedure in the model. Teachers help students during training; 4th - Student assessment based on a checklist form. Feedback and correction of wrong actions. Results: Students expressed interest in learning ICP monitoring. Tests concerning the hit rate are still being performed. ICP's final results and video will be shown at the event. Conclusion: The study of intracranial pressure measurement based on an experimental model consists of an effective and controlled method of learning and research, more appropriate for teaching neurointensive care practices. Assessment based on a checklist form helps teachers keep track of student learning progress. This project offers medical students a safe method to develop intensive neurological monitoring skills for clinical assessment of patients with neurological disorders.

Keywords: neurology, intracranial pressure, medical education, simulation

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Authors: Thomas Doutre, Emmanuel De Meric De Bellefon

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This paper describes the application of local-search metaheuristic quantum annealing to portfolio opti- mization. Heuristic technics are particularly handy when Markowitz’ classical Mean-Variance problem is enriched with additional realistic constraints. Once tailored to the problem, computational experiments on real collected data have shown the superiority of quantum annealing over simulated annealing for this constrained optimization problem, taking advantages of quantum effects such as tunnelling.

Keywords: optimization, portfolio risk management, quantum annealing, metaheuristic

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Authors: B. J. Sandesh, Saurabha Jirgi, S. Vidya, Prakash Eljer, Gowri Srinivasa

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In this paper, we propose a framework to help users to search and retrieve the portions in the lecture video of their interest. This is achieved by temporally segmenting and indexing the lecture video using the topic keywords. We use transcribed text from the video and documents relevant to the video topic extracted from the web for this purpose. The keywords for indexing are found by applying the non-negative matrix factorization (NMF) topic modeling techniques on the web documents. Our proposed technique first creates indices on the transcribed documents using the topic keywords, and these are mapped to the video to find the start and end time of the portions of the video for a particular topic. This time information is stored in the index table along with the topic keyword which is used to retrieve the specific portions of the video for the query provided by the users.

Keywords: video indexing and retrieval, lecture videos, content based video search, multimodal indexing

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Authors: M. Taibeche, L. Guerbous, M. Kechouane, R. Nedjar, T. Zergoug

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It is known that Y2O3 Material is the most important among the sesquioxides within the general class of refractory ceramics. Indeed, this compound has many applications such as sintering optical windows, components for rare-earth doped lasers as well as inorganic scintillators in the detection scintillation. In particular Eu2+ and Ce3+ are favored dopants in many the scintillators due to its allowed optical 5d-4f transition. In this work, we present new results concerning structural and electronic properties of Ce-doped Y2O3, investigated by density functional theory (DFT), using the Heyd–Scuseria–Ernzerhof (HSE) hybrid functional and DFT+U two approaches. When, we compared the results from the two methods we obtain a good agreement available experimental data. Furthermore, the effect of cerium on the material has also been studied and discussed in the same framework.

Keywords: DFT, vienne ab initio simulation packages, scintillators, Heyd–Scuseria–Ernzerhof (HSE) hybrid functional

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Authors: C. Yin, B. Zhang, Y. Liu, J. Cai

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Airborne EM (AEM) is an effective geophysical exploration tool, especially suitable for ridged mountain areas. In these areas, topography will have serious effects on AEM system responses. However, until now little study has been reported on topographic effect on airborne EM systems. In this paper, an edge-based unstructured finite-element (FE) method is developed for 3D topographic modeling for both frequency and time-domain airborne EM systems. Starting from the frequency-domain Maxwell equations, a vector Helmholtz equation is derived to obtain a stable and accurate solution. Considering that the AEM transmitter and receiver are both located in the air, the scattered field method is used in our modeling. The Galerkin method is applied to discretize the Helmholtz equation for the final FE equations. Solving the FE equations, the frequency-domain AEM responses are obtained. To accelerate the calculation speed, the response of source in free-space is used as the primary field and the PARDISO direct solver is used to deal with the problem with multiple transmitting sources. After calculating the frequency-domain AEM responses, a Hankel’s transform is applied to obtain the time-domain AEM responses. To check the accuracy of present algorithm and to analyze the characteristic of topographic effect on airborne EM systems, both the frequency- and time-domain AEM responses for 3 model groups are simulated: 1) a flat half-space model that has a semi-analytical solution of EM response; 2) a valley or hill earth model; 3) a valley or hill earth with an abnormal body embedded. Numerical experiments show that close to the node points of the topography, AEM responses demonstrate sharp changes. Special attentions need to be paid to the topographic effects when interpreting AEM survey data over rugged topographic areas. Besides, the profile of the AEM responses presents a mirror relation with the topographic earth surface. In comparison to the topographic effect that mainly occurs at the high-frequency end and early time channels, the EM responses of underground conductors mainly occur at low frequencies and later time channels. For the signal of the same time channel, the dB/dt field reflects the change of conductivity better than the B-field. The research of this paper will serve airborne EM in the identification and correction of the topographic effects.

Keywords: 3D, Airborne EM, forward modeling, topographic effect

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Authors: Aymen Arfaoui, Abdelkader Soumaya, Ali Kadri, Noureddine Ben Ayed

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The major contractional events characterized by strike-slip faulting, folding, and thrusting occurred in the Eocene, Late Miocene, and Quaternary along with the NE Tunisian domain between Bou Kornine-Ressas- Msella and Cap Bon Peninsula. During the Plio-Quaternary, the Grombalia and Mornag grabens show a maximum of collapse in parallelism with the NNW-SSE SHmax direction and developed as 3rd order extensive regions within a regional compressional regime. Using available tectonic and geophysical data supplemented by new fault-kinematic observations, we show that Cenozoic deformations are dominated by first order N-S faults reactivation, this sinistral wrench system is responsible for the formation of strike-slip duplexes, thrusts, folds, and grabens. Based on our new structural interpretation, the major faults of N-S Axis, Bou Kornine-Ressas-Messella (MRB), and Hammamet-Korbous (HK) form an N-S first order restraining stepover within a left-lateral strike-slip duplex. The N-S master MRB fault is dominated by contractional imbricate fans, while the parallel HK fault is characterized by a trailing of extensional imbricate fans. The Eocene and Miocene compression phases in the study area caused sinistral strike-slip reactivation of pre-existing N-S faults, reverse reactivation of NE-SW trending faults, and normal-oblique reactivation of NW-SE faults, creating a NE-SW to N-S trending system of east-verging folds and overlaps. Seismic tomography images reveal a key role for the lithospheric subvertical tear or STEP fault (Slab Transfer Edge Propagator) evidenced below this region on the development of the MRB and the HK relay zone. The presence of extensive syntectonic Pliocene sequences above this crustal scale fault may be the result of a recent lithospheric vertical motion of this STEP fault due to the rollback and lateral migration of the Calabrian slab eastward.

Keywords: Tunisia, strike-slip fault, contractional duplex, tectonic stress, restraining stepover, STEP fault

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Authors: Allan F. F. Alves, Fernando A. Bacchim Neto, Guilherme Giacomini, Marcela de Oliveira, Ana L. M. Pavan, Maria E. D. Rosa, Diana R. Pina

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Stroke is a worldwide concern, only in Brazil it accounts for 10% of all registered deaths. There are 2 stroke types, ischemic (87%) and hemorrhagic (13%). Early diagnosis is essential to avoid irreversible cerebral damage. Non-enhanced computed tomography (NECT) is one of the main diagnostic techniques used due to its wide availability and rapid diagnosis. Detection depends on the size and severity of lesions and the time spent between the first symptoms and examination. The Alberta Stroke Program Early CT Score (ASPECTS) is a subjective method that increases the detection rate. The aim of this work was to implement an image segmentation system to enhance ischemic stroke and to quantify the area of ischemic and hemorrhagic stroke lesions in CT scans. We evaluated 10 patients with NECT examinations diagnosed with ischemic stroke. Analyzes were performed in two axial slices, one at the level of the thalamus and basal ganglion and one adjacent to the top edge of the ganglionic structures with window width between 80 and 100 Hounsfield Units. We used different image processing techniques such as morphological filters, discrete wavelet transform and Fuzzy C-means clustering. Subjective analyzes were performed by a neuroradiologist according to the ASPECTS scale to quantify ischemic areas in the middle cerebral artery region. These subjective analysis results were compared with objective analyzes performed by the computational algorithm. Preliminary results indicate that the morphological filters actually improve the ischemic areas for subjective evaluations. The comparison in area of the ischemic region contoured by the neuroradiologist and the defined area by computational algorithm showed no deviations greater than 12% in any of the 10 examination tests. Although there is a tendency that the areas contoured by the neuroradiologist are smaller than those obtained by the algorithm. These results show the importance of a computer aided diagnosis software to assist neuroradiology decisions, especially in critical situations as the choice of treatment for ischemic stroke.

Keywords: ischemic stroke, image processing, CT scans, Fuzzy C-means

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Authors: Gayathri Pramod, Sheeja K. P.

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Urban flooding has been seen rising in cities for the past few years. This rise in urban flooding is the result of increasing urbanization and increasing climate change. A resilient city design focuses on 'living with water'. This means that the city is capable of accommodating the floodwaters without having to risk any loss of lives or properties. The resilient city design incorporates green infrastructure, river edge treatment, open space design, etc. to form a city that functions as a whole for resilience. Sponge urbanism is a recent method for building resilient cities and is founded by China in 2014. Sponge urbanism is the apt method for resilience building for a tropical town like Aluva of Kerala. Aluva is a tropical town that experiences rainfall of about 783 mm per month during the rainy season. Aluva is an urbanized town which faces the risk of urban flooding and riverine every year due to the presence of Periyar River in the town. Impervious surfaces and hard construction and developments contribute towards flood risk by posing as interference for a natural flow and natural filtration of water into the ground. This type of development is seen in Aluva also. Aluva is designed in this research as a town that have resilient strategies of sponge city and which focusses on natural methods of construction. The flood susceptibility of Aluva is taken into account to design the spaces for sponge urbanism and in turn, reduce the flood susceptibility for the town. Aluva is analyzed, and high-risk zones for development are identified through studies. These zones are designed to withstand the risk of flooding. Various catchment areas are identified according to the natural flow of water, and then these catchment areas are designed to act as a public open space and as detention ponds in case of heavy rainfall. Various development guidelines, according to land use, is also prescribed, which help in increasing the green cover of the town. Aluva is then designed to be a completely flood-adapted city or sponge city according to the guidelines and interventions.

Keywords: climate change, flooding, resilient city, sponge city, sponge urbanism, urbanization

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Authors: Mohamed Barbary, Mohamed H. Abd El-Azeem

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Maneuvering extended object tracking (M-EOT) using high-resolution inverse synthetic aperture radar (ISAR) observations has been gaining momentum recently. This work presents a new robust implementation of the multiple models (MM) multi-Bernoulli (MB) filter for M-EOT, where the M-EOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, MM-MB-TBD filter

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Authors: Sam Zhang

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The landscape of Opto mechatronics is viewed along the line of light vs. matter, photonics vs. semiconductors, and optics vs. mechatronics. Optomechatronics is redefined as the integration of light and matter from the atom, device, and system to the application. The markets and megatrends in Opto mechatronics are further listed. The author then focuses on Opto mechatronic technology in the semiconductor industry as an example and reviews the practical systems, characteristics, and trends. Opto mechatronics, together with photonics and semiconductor, will continue producing the computational and smart infrastructure required for the 4th industrial revolution.

Keywords: photonics, semiconductor, optomechatronics, 4th industrial revolution

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Authors: Ivan P. Pozdnyakov, Alexey A. Melnikov, Nikolai V. Tkachenko

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Photochemical reactions with participation of iron (III) carboxylates are important for environmental photochemistry and have a great potential of application in water purification (Advanced Oxidation Processes, photo-Fenton and Fenton-like processes). In spite of this information about excited states and primary intermediates in photochemistry of Fe(III) complexes with carboxylic acids is scarce. This talk presents and discusses the results of several recent authors' publications in a field of ultra fast spectroscopy of natural Fe(III) carboxylates.

Keywords: carboxylates, iron complexes, photochemistry, radical complexes, ultrafast processes

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Authors: Kailas L. Wasewar

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Biobutanol has been considered as a potential and alternative biofuel relative to the most popular biodiesel and bioethanol. End product toxicity is the major problems in commercialization of fermentation based process which can be reduce to some possible extent by removing biobutanol simultaneously. Several techniques have been investigated for removing butanol from fermentation broth such as stripping, adsorption, liquid–liquid extraction, pervaporation, and membrane solvent extraction. Liquid–liquid extraction can be performed with high selectivity and is possible to carry out inside the fermenter. Conventional solvents have few drawbacks including toxicity, loss of solvent, high cost etc. Hence alternative solvents must be explored for the same. Room temperature ionic liquids (RTILs) composed entirely of ions are liquid at room temperature having negligible vapor pressure, non-flammability, and tunable physiochemical properties for a particular application which term them as “designer solvents”. Ionic liquids (ILs) have recently gained much attention as alternatives for organic solvents in many processes. In particular, ILs have been used as alternative solvents for liquid–liquid extraction. Their negligible vapor pressure allows the extracted products to be separated from ILs by conventional low pressure distillation with the potential for saving energy. Morpholinium, imidazolium, ammonium, phosphonium etc. based ionic liquids have been employed for the separation biobutanol. In present chapter, basic concepts of ionic liquids and application in separation have been presented. Further, type of ionic liquids including, conventional, functionalized, polymeric, supported membrane, and other ionic liquids have been explored. Also the effect of various performance parameters on separation of biobutanol by ionic liquids have been discussed and compared for different cation and anion based ionic liquids. The typical methodology for investigation have been adopted such as contacting the equal amount of biobutanol and ionic liquids for a specific time say, 30 minutes to confirm the equilibrium. Further, biobutanol phase were analyzed using GC to know the concentration of biobutanol and material balance were used to find the concentration in ionic liquid.

Keywords: biobutanol, separation, ionic liquids, sustainability, biorefinery, waste biomass

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Authors: Nurazean Maarop, Noorjan Mohd Mustapha, Rasimah Yusoff, Roslina Ibrahim, Norziha Megat Mohd Zainuddin

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The goal of this study is to identify success factors that could influence the ISMS self-implementation in government sector from qualitative perspective. This study is based on a case study in one of the Malaysian government agency. Semi-structured interviews involving five key informants were conducted to examine factors addressed in the conceptual framework. Subsequently, thematic analysis was executed to describe the influence of each factor on the success implementation of ISMS. The result of this study indicates that management commitment, implementer commitment and implementer competency are part of the success factors for ISMS self-implementation in Malaysian Government Sector.

Keywords: ISMS success factors, IT project management, IS success, information security

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Authors: Anita Richter

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Innovation is one of the key foundations of competitive advantage, generating growth and welfare worldwide. Consequently, all firms should innovate to bring new ideas to the market. Innovation is a vital growth driver, particularly for transition countries to move towards knowledge-based, high-income economies. However, numerous barriers, such as financial, regulatory or infrastructural constraints prevent, in particular, new and small firms in transition countries from innovating. Thus SMEs’ innovation output may benefit substantially from government support. This research paper aims to assess the effect of government interventions on innovation activities in SMEs in emerging countries. Until now academic research related to the innovation policies focused either on single country and/or high-income countries assessments and less on cross-country and/or low and middle-income countries. Therefore the paper seeks to close the research gap by providing empirical evidence from 8,500 firms in 15 transition countries (Eastern Europe, South Caucasus, South East Europe, Middle East and North Africa). Using firm-level data from the Business Environment and Enterprise Performance Survey of the World Bank and EBRD and policy data from the SME Policy Index of the OECD, the paper investigates how government interventions affect SME’s likelihood of investing in any technological and non-technological innovation. Using the Standard Linear Regression, the impact of government interventions on SMEs’ innovation output and R&D activities is measured. The empirical analysis suggests that a firm’s decision to invest into innovative activities is sensitive to government interventions. A firm’s likelihood to invest into innovative activities increases by 3% to 8%, if the innovation eco-system noticeably improves (measured by an increase of 1 level in the SME Policy Index). At the same time, a better eco-system encourages SMEs to invest more in R&D. Government reforms in establishing a dedicated policy framework (IP legislation), institutional infrastructure (science and technology parks, incubators) and financial support (public R&D grants, innovation vouchers) are particularly relevant to stimulate innovation performance in SMEs. Particular segments of the SME population, namely micro and manufacturing firms, are more likely to benefit from an increased innovation framework conditions. The marginal effects are particularly strong on product innovation, process innovation, and marketing innovation, but less on management innovation. In conclusion, government interventions supporting innovation will likely lead to higher innovation performance of SMEs. They increase productivity at both firm and country level, which is a vital step in transitioning towards knowledge-based market economies.

Keywords: innovation, research and development, government interventions, economic development, small and medium-sized enterprises, transition countries

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Authors: Gabriela Wyszogrodzka, Przemyslaw Dorozynski, Barbara Gil, Maciej Strzempek, Bartosz Marszalek, Piotr Kulinowski, Wladyslaw Piotr Weglarz, Elzbieta Menaszek

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MOFs (Metal-Organic Frameworks) belong to a new group of porous materials with a hybrid organic-inorganic construction. Their structure is a network consisting of metal cations or clusters (acting as metallic centers, nodes) and the organic linkers between nodes. The interest in MOFs is primarily associated with the use of their well-developed surface and large porous. Possibility to build MOFs of biocompatible components let to use them as potential drug carriers. Furthermore, forming MOFs structure from cations possessing paramagnetic properties (e.g. iron cations) allows to use them as MRI (Magnetic Resonance Imaging) contrast agents. The concept of formation of particles that combine the ability to transfer active substance with imaging properties has been called theranostic (from words combination therapy and diagnostics). By building MOF structure from iron cations it is possible to use them as theranostic agents and monitoring the distribution of the active substance after administration in real time. In the study iron-MOF: Fe-MIL-101-NH2 was chosen, consisting of iron cluster in nodes of the structure and amino-terephthalic acid as a linker. The aim of the study was to investigate the possibility of applying Fe-MIL-101-NH2 as inhalable theranostic particulate system for the first-line anti-tuberculosis antibiotic – isoniazid. The drug content incorporated into Fe-MIL-101-NH2 was evaluated by dissolution study using spectrophotometric method. Results showed isoniazid encapsulation efficiency – ca. 12.5% wt. Possibility of Fe-MIL-101-NH2 application as the MRI contrast agent was demonstrated by magnetic resonance tomography. FeMIL-101-NH2 effectively shortening T1 and T2 relaxation times (increasing R1 and R2 relaxation rates) linearly with the concentrations of suspended material. Images obtained using multi-echo magnetic resonance imaging sequence revealed possibility to use FeMIL-101-NH2 as positive and negative contrasts depending on applied repetition time. MOFs micronization via ultrasound was evaluated by XRD, nitrogen adsorption, FTIR, SEM imaging and did not influence their crystal shape and size. Ultrasonication let to break the aggregates and achieve very homogeneously looking SEM images. MOFs cytotoxicity was evaluated in in vitro test with a highly sensitive resazurin based reagent PrestoBlue™ on L929 fibroblast cell line. After 24h no inhibition of cell proliferation was observed. All results proved potential possibility of application of ironMOFs as an isoniazid carrier and as MRI contrast agent in inhalatory treatment of tuberculosis. Acknowledgments: Authors gratefully acknowledge the National Science Center Poland for providing financial support, grant no 2014/15/B/ST5/04498.

Keywords: imaging agents, metal-organic frameworks, theranostics, tuberculosis

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Authors: Kung-Jen Tu, Danny Vernatha

Abstract:

To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: database, electricity sub-meters, energy anomaly detection, sensor

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Authors: Hussen Nasir, Mohd Fitri Mansor, Noor Hidayah Abu

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Liberation of the SME market led to a dynamic competitive business environment. SMEs are considered as an engine for economic growth of most nations. SMEs must be willing to adopt the latest technology and incorporate innovation as part of their business strategies. The aim of this study is to examine the innovation practices (innovation strategy and innovation culture) towards sustaining SME’s performance and the moderating effect of intellectual capital on the relationship of innovation practices on SME’s performance. The study will identify the strongest variables that influence the SMEs performance and proposed several hypothesis toward innovation and intellectual capital. Finally, the study will propose a theoretical framework. The current study will contribute to the knowledge of important on the element of intellectual capital as well as innovation practices in the SMEs performance.

Keywords: intellectual capital, innovation practices, SMEs, performance, innovation strategy, innovation culture

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Authors: Shrabani Ghosh

Abstract:

Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Samar Swaid

Abstract:

Today, corporates are moving toward the adoption of Design-Thinking techniques to develop products and services, putting their consumer as the heart of the development process. One of the leading companies in Design-Thinking, IDEO (Innovation, Design, Engineering Organization), defines Design-Thinking as an approach to problem-solving that relies on a set of multi-layered skills, processes, and mindsets that help people generate novel solutions to problems. Design thinking may result in new ideas, narratives, objects or systems. It is about redesigning systems, organizations, infrastructures, processes, and solutions in an innovative fashion based on the users' feedback. Tim Brown, president and CEO of IDEO, sees design thinking as a human-centered approach that draws from the designer's toolkit to integrate people's needs, innovative technologies, and business requirements. The application of design thinking has been witnessed to be the road to developing innovative applications, interactive systems, scientific software, healthcare application, and even to utilizing Design-Thinking to re-think business operations, as in the case of Airbnb. Recently, there has been a movement to apply design thinking to machine learning and artificial intelligence to ensure creating the "wow" effect on consumers. The Association of Computing Machinery task force on Data Science program states that" Data scientists should be able to implement and understand algorithms for data collection and analysis. They should understand the time and space considerations of algorithms. They should follow good design principles developing software, understanding the importance of those principles for testability and maintainability" However, this definition hides the user behind the machine who works on data preparation, algorithm selection and model interpretation. Thus, the Data Science program includes design thinking to ensure meeting the user demands, generating more usable machine learning tools, and developing ways of framing computational thinking. Here, describe the fundamentals of Design-Thinking and teaching modules for data science programs.

Keywords: data science, design thinking, AI, currculum, transformation

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Authors: Wafa Al Jabri

Abstract:

Background: In Middle Eastern Countries (MECs), there is a high prevalence of genetic blood disorders (GBDs), particularly sickle cell disease and thalassemia. The GBDs are considered a major public health concern that place a huge burden to individuals, families, communities, and health care systems. The high rates of consanguineous marriages, along with the unacceptable termination of at-risk pregnancy in MECs, reduce the possible solutions to control the high prevalence of GBDs. Since the early 1970s, most of MECs have started introducing premarital screening services (PSS) as a preventive measure to identify the asymptomatic carriers of GBDs and to provide genetic counseling to help couples plan for healthy families; yet, the success rate of PSS is very low. Purpose: This paper aims to highlight the factors that affect the success of PSS in MECs. Methods: An integrative review of articles located in CINAHL, PubMed, SCOPUS, and MedLine was carried out using the following terms: “premarital screening,” “success,” “effectiveness,” and “ genetic blood disorders”. Second, a hand search of the reference lists and Google searches were conducted to find studies that did not exist in the primary database searches. Only studies which are conducted in MECs and published after 2010 were included. Studies that were not published in English were excluded. Results: Eighteen articles were included in the review. The results showed that PSS in most of the MECs was successful in achieving its objective of identifying high-risk marriages; however, the service failed to meet its ultimate goal of reducing the prevalence of GBDs. Various factors seem to hinder the success of PSS, including poor public awareness, late timing of the screening, culture and social stigma, lack of prenatal diagnosis services and therapeutic abortion, emotional factors, religious beliefs, and lack of genetic counseling services. However, poor public awareness, late timing of the screening, religious misbeliefs, and the lack of adequate counseling services were the most common barriers identified. Conclusion and Implications: The review help in providing a framework for an effective preventive measure to reduce the prevalence of GBDs in MECS. This framework focuses primarily in overcoming the identified barriers by providing effective health education programs in collaboration with religious leaders, offering the screening test to young adults at an earlier stage, and tailoring the genetic counseling to consider people’s values, beliefs, and preferences.

Keywords: premarital screening, middle east, genetic blood disorders, factors

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Authors: Mohd Yazid M. Yunos, R. Arinah, Nor Kalsum M. Isa, U. Nangkula, Nor A. Ismail, Nor F. Ariffin

Abstract:

Islamic City planning is a concept of optimizing the overall arrangement of land use without compromising community. The concept was influenced by the specific intentions in mind, applying certain ideological principles and objectives rooted in Islamic faith and Muslim culture using distinct design elements. Holy Quran and hadiths provide a foundation for understanding Islamic Principles as clearly shared by the established Islamic Cities such as Medina, Mecca and Jerusalem. This paper aimed to explore the principles and elements of an Islamic City through the review of relevant literature by the means of Content Analysis method. A theoretical framework of Islamic City Principles was then formulated to be the main outcome of the study. The finding is very important to be a useful starting point for future study, especially for formulating a clear guide for the development of upcoming Islamic City in Malaysia.

Keywords: Islamic principles, sustainable city planning, Islamic city, Malaysia

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Authors: Djemai Bara, Mohamed Faouzi Mahboub, Djamila Bennaceur-Doumaz

Abstract:

In this work, the role of the preformed plasma created on the front face of a target, irradiated by a high intensity short pulse laser, in the framework of ion acceleration process, modeled by Target Normal Sheath Acceleration (TNSA) mechanism, is studied. This plasma is composed of cold ions governed by fluid equations and non-thermal & trapped with densities represented by a "Cairns-Gurevich" equation. The self-similar solution of the equations shows that electronic trapping and the presence of non-thermal electrons in the pre-plasma are both responsible in ion acceleration as long as the proportion of energetic electrons is not too high. In the case where the majority of electrons are energetic, the electrons are accelerated directly by the ponderomotive force of the laser without the intermediate of an accelerating plasma wave.

Keywords: Cairns-Gurevich Equation, ion acceleration, plasma expansion, pre-plasma

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